Senior AI/LLM Architect & Developer — Conversational Digital Health Platform
Project evidence involving Python, OpenAI API, RAG. First observed 3 Sept 2026; the response opens on upwork.com.
- Budget
- Not provided by source
- Work format
- Project
- Role family
- AI / ML engineer
- Seniority
- Senior
- Observed
- 3 Sept 202655 days old
- Deadline status
- Deadline not provided — verify source
- Response destination
- upwork.com
Opportunity summary
Senior AI/LLM Architect & Developer — Conversational Digital Health Platform. The source classifies this as project work involving Python, OpenAI API, RAG, Tool/function calling, Vector search and knowledge systems. Location or remote eligibility: Worldwide remote. Exceptional individual developers and small specialized AI teams/agencies are explicitly welcomed; the actual technical architect must be named and directly accessible..
Technology and scope
The reported stack is OpenAI, Gemini, Anthropic Claude, DeepSeek, Python/backend, databases, RAG, vector search, structured outputs/tool calling, long-term memory, voice AI, cloud, GDPR, authentication, encryption. Check the source for required versions, deliverables and which technologies are mandatory.
Engagement details
Project: a defined delivery outcome rather than an open-ended employment relationship. Source timing: 6+ months; more than 30 h/week; starts with a small paid discovery assignment
Budget
Budget not provided by source. Confirm the rate or project value before preparing a proposal; no estimate has been substituted.
Dates and availability
First observed by Leadiy on 3 Sept 2026, 15:30 UTC. Public since 14 Sept 2026, 00:30 UTC. Deadline not provided — verify source. A listed deadline does not confirm that applications are still accepted. These are observation and publication dates, not a reconstruction of the source posting date. Date-only deadlines have no supplied timezone; the date changes here at midnight UTC.
Related market context
In the current 30-day Hiring Pulse, Python appears in 70 of 325 observed opportunities (21.5%). Counts are multi-label, so one opportunity may contribute to several technology buckets. This is a separate aggregate sample, not a confirmation of this opportunity’s availability.
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